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Founded in 1977 as the Senior Care Action Network, SCAN began with a simple but radical idea: that older adults deserve to stay healthy and independent. That belief was championed by a group of community activists we still honor today as the “12 Angry Seniors.” Their mission continues to guide everything we do.
Today, SCAN is a nonprofit health organization serving more than 500,000 people across Arizona, California, Nevada, New Mexico, Texas, and Washington, with over $8 billion in annual revenue. With nearly five decades of experience, we have built a distinctive, values-driven platform dedicated to improving care for older adults.
Our work spans Medicare Advantage, fully integrated care models, primary care, care for the most medically and socially complex populations, and next-generation care delivery models. Across all of this, we are united by a shared commitment: combining compassion with discipline, innovation with stewardship, and growth with integrity.
At SCAN, we believe scale should strengthen—not dilute—our mission. We are building the future of care for older adults, grounded in purpose, accountability, and respect for the people and communities we serve.
The Job
In this role, you will help advance SCAN’s AI enablement and enterprise data governance practices. This role is responsible for improving the trust, usability, and business context richness of data that powers AI, analytics, reporting, and operational decision-making.
This role helps build the foundation for enterprise AI by strengthening core knowledge management capabilities via the development, governance, and adoption of enterprise data assets and knowledge structures, including business glossaries, governed metrics, semantic layers, ontologies, knowledge graphs, metadata, lineage, and stewardship practices. You will work closely with data stewards, subject matter experts, platform teams, and executive business leaders to build context, standardize business terminology, improve data quality, and make enterprise data easier for people and AI-enabled tools to understand and use.
This is an essential role as SCAN modernizes its data ecosystem through a modern platform, scalable self-service analytics, and AI-assisted ways of working.
You Will
- Enhance SCAN’s semantic foundation by developing dimensional models, hierarchies, domain relationships, and governed metrics that enable consistent AI use cases.
- Support ontology and knowledge graph initiatives by identifying key business entities, relationships, synonyms, and domain concepts that improve data connectivity, searchability, and AI comprehension.
- Govern and document data assets across Snowflake, Databricks, and Iceberg environments to ensure structured and semi-structured data is well-described, discoverable, and trusted for analytics and AI workflows.
- Maintain and enrich the enterprise data catalog, documenting metadata, lineage, ownership, usage context, and business meaning for high-value data assets.
- Improve data discoverability and usability through tagging, glossary management, workflow optimization, and metadata quality controls.
- Perform data and metric validation to assess accuracy, completeness, aggregation logic, consistency, and timeliness across data products, including via the use of AI-assisted tools.
- Partner with business stakeholders, data stewards, subject matter experts, analytics teams, and technical teams to execute enterprise data governance and AI-readiness priorities across key domains.
- Investigate data quality issues, conduct root cause analysis, document business impact, and partner with data engineering, analytics, reporting, and business teams to support resolution.
- Participate in Agile ceremonies to ensure governance and AI enablement work is visible, prioritized, and delivered effectively.
- Drive continuous improvement in governance automation, stewardship workflows, reporting certification, and AI-assisted governance capabilities.
- We seek Rebels who are curious about AI and its power to transform how we operate, improve decision-making, and serve our members.
- Actively support the achievement of SCAN’s Vision and Goals.
- Other duties as assigned.
Your qualifications
- Bachelor's degree in information systems, Data Analytics, Computer Science, Business Administration, Healthcare Administration, Statistics, or a related field; equivalent experience may be considered.
- 3+ years of experience in data engineering, data governance, data management, data quality, analytics, business intelligence, metadata management, knowledge management, or related data-focused role.
- Experience in the health care industry, especially in areas such as Medicare Advantage, clinical analytics, medical economics, quality, pharmacy, claims, provider, member, or operational data environments, is strongly preferred.
- Experience with modern knowledge management techniques such as semantic layers, ontologies, knowledge graphs, retrieval-augmented generation, AI-assisted documentation, or metadata-driven discovery preferred.
- Familiarity with modern warehouse and open Lakehouse concepts, including cloud object storage, open table formats such as Apache Iceberg or Delta Lake, metadata catalogs, data sharing, lineage, and governance of structured and semi-structured data.
- Familiarity with using AI-assisted tools to improve documentation, analysis, data discovery, metadata quality, and governance workflows.
- Experience with enterprise data catalog, metadata management, data lineage, business glossary, stewardship, and/or or report certification practices.
- Experience with BI and reporting platforms such as Power BI, Tableau, SSRS, or similar tools.
- Experience with CLI tools such as Cortex Code, Claude Code, or similar.
- Experience working in SAFe Agile or another Agile delivery framework.
- Preferred certifications include CDMP, DGSP, DCAM, DAMA-related training, Snowflake certification, Microsoft Power BI certification, or relevant Agile/SAFe certifications.
Competencies
- Knowledge Management Mindset: Helps organize business meaning, definitions, relationships, ownership, and metadata so that enterprise data is easier to find, understand, govern, and reuse.
- Business Partnership: Builds trusted relationships with business and technical stakeholders and translates governance, data quality, and AI-readiness practices into business value.
- Analytical Thinking: Uses structured analysis to evaluate data issues, identify root causes, assess business impact, and improve trust in data used for analytics and AI-enabled capabilities.
- Governance Discipline: Applies consistent standards for definitions, metadata, quality rules, stewardship, lineage, and documentation.
- Communication: Explains complex data concepts clearly to both technical and non-technical audiences.
- Continuous Improvement: Identifies opportunities to improve governance workflows, data usability, automation, AI-assisted documentation and scalable self-service analytics.
Skills & Abilities
- Ability to support semantic layer and metrics governance, including standardized definitions, dimensional concepts, hierarchies, measure consistency, and policy adherence.
- Familiarity with knowledge management concepts such as ontologies, knowledge graphs, taxonomies, and domain models.
- Ability to translate technical data structures into clear, business-aligned definitions and documentation, especially via data dictionaries, catalog entries, report inventories, data quality findings, and usage context.
- Strong SQL skills for data profiling, validation, reconciliation, and issue investigation.
- Familiarity with Snowflake, SQL Server, Power BI, Tableau, SSRS, data catalogs, modern analytics platforms, and open lakehouse concepts such as cloud object storage, open table formats, metadata catalogs, and governed data access.
- Ability to work effectively across business, analytics, data engineering, platform, stewardship, and leadership teams.
- Practical understanding of healthcare data domains such as claims, membership, providers, clinical operations, pharmacy, quality, utilization management, or finance preferred.
- Ability to manage multiple priorities in an Agile environment while maintaining attention to detail.
- Awareness of emerging automation, AI-assisted documentation, data quality monitoring, semantic search, and governed by self-service analytics capabilities.
What's in it for you?
Base Salary Range: $80,300 to $138,330 annually
An annual employee bonus program
Robust Wellness Program
Generous paid-time-off (PTO)
11 paid holidays per year, 1 floating holiday, birthday off, and 2 volunteer days
Excellent 401(k) Retirement Saving Plan with employer match
Robust employee recognition program
Tuition reimbursement
An opportunity to become part of a team that makes a difference to our members and our community every day!
We're always looking for talented people to join our team! Qualified applicants are encouraged to apply now!
At SCAN we believe that it is our business to improve the state of our world. Each of us has a responsibility to drive Equality in our communities and workplaces. We are committed to creating a workforce that reflects our community through inclusive programs and initiatives such as equal pay, employee resource groups, inclusive benefits, and more.
SCAN is proud to be an Equal Employment Opportunity and Affirmative Action workplace. Individuals seeking employment will receive consideration for employment without regard to race, color, national origin, religion, age, sex (including pregnancy, childbirth or related medical conditions), sexual orientation, gender perception or identity, age, marital status, disability, protected veteran status or any other status protected by law. A background check is required.
#LI-JB1 #LI-Hybrid
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information. 41 CFR 60-1.35(c)
Founded in 1977 as the Senior Care Action Network, SCAN began with a simple but radical idea: that older adults deserve to stay healthy and independent. That belief was championed by a group of community activists we still honor today as the “12 Angry Seniors.” Their mission continues to guide everything we do.
Today, SCAN is a nonprofit health organization serving more than 500,000 people across Arizona, California, Nevada, New Mexico, Texas, and Washington, with over $8 billion in annual revenue. With nearly five decades of experience, we have built a distinctive, values-driven platform dedicated to improving care for older adults.
Our work spans Medicare Advantage, fully integrated care models, primary care, care for the most medically and socially complex populations, and next-generation care delivery models. Across all of this, we are united by a shared commitment: combining compassion with discipline, innovation with stewardship, and growth with integrity.
At SCAN, we believe scale should strengthen—not dilute—our mission. We are building the future of care for older adults, grounded in purpose, accountability, and respect for the people and communities we serve.
The Job
In this role, you will help advance SCAN’s AI enablement and enterprise data governance practices. This role is responsible for improving the trust, usability, and business context richness of data that powers AI, analytics, reporting, and operational decision-making.
This role helps build the foundation for enterprise AI by strengthening core knowledge management capabilities via the development, governance, and adoption of enterprise data assets and knowledge structures, including business glossaries, governed metrics, semantic layers, ontologies, knowledge graphs, metadata, lineage, and stewardship practices. You will work closely with data stewards, subject matter experts, platform teams, and executive business leaders to build context, standardize business terminology, improve data quality, and make enterprise data easier for people and AI-enabled tools to understand and use.
This is an essential role as SCAN modernizes its data ecosystem through a modern platform, scalable self-service analytics, and AI-assisted ways of working.
You Will
- Enhance SCAN’s semantic foundation by developing dimensional models, hierarchies, domain relationships, and governed metrics that enable consistent AI use cases.
- Support ontology and knowledge graph initiatives by identifying key business entities, relationships, synonyms, and domain concepts that improve data connectivity, searchability, and AI comprehension.
- Govern and document data assets across Snowflake, Databricks, and Iceberg environments to ensure structured and semi-structured data is well-described, discoverable, and trusted for analytics and AI workflows.
- Maintain and enrich the enterprise data catalog, documenting metadata, lineage, ownership, usage context, and business meaning for high-value data assets.
- Improve data discoverability and usability through tagging, glossary management, workflow optimization, and metadata quality controls.
- Perform data and metric validation to assess accuracy, completeness, aggregation logic, consistency, and timeliness across data products, including via the use of AI-assisted tools.
- Partner with business stakeholders, data stewards, subject matter experts, analytics teams, and technical teams to execute enterprise data governance and AI-readiness priorities across key domains.
- Investigate data quality issues, conduct root cause analysis, document business impact, and partner with data engineering, analytics, reporting, and business teams to support resolution.
- Participate in Agile ceremonies to ensure governance and AI enablement work is visible, prioritized, and delivered effectively.
- Drive continuous improvement in governance automation, stewardship workflows, reporting certification, and AI-assisted governance capabilities.
- We seek Rebels who are curious about AI and its power to transform how we operate, improve decision-making, and serve our members.
- Actively support the achievement of SCAN’s Vision and Goals.
- Other duties as assigned.
Your qualifications
- Bachelor's degree in information systems, Data Analytics, Computer Science, Business Administration, Healthcare Administration, Statistics, or a related field; equivalent experience may be considered.
- 3+ years of experience in data engineering, data governance, data management, data quality, analytics, business intelligence, metadata management, knowledge management, or related data-focused role.
- Experience in the health care industry, especially in areas such as Medicare Advantage, clinical analytics, medical economics, quality, pharmacy, claims, provider, member, or operational data environments, is strongly preferred.
- Experience with modern knowledge management techniques such as semantic layers, ontologies, knowledge graphs, retrieval-augmented generation, AI-assisted documentation, or metadata-driven discovery preferred.
- Familiarity with modern warehouse and open Lakehouse concepts, including cloud object storage, open table formats such as Apache Iceberg or Delta Lake, metadata catalogs, data sharing, lineage, and governance of structured and semi-structured data.
- Familiarity with using AI-assisted tools to improve documentation, analysis, data discovery, metadata quality, and governance workflows.
- Experience with enterprise data catalog, metadata management, data lineage, business glossary, stewardship, and/or or report certification practices.
- Experience with BI and reporting platforms such as Power BI, Tableau, SSRS, or similar tools.
- Experience with CLI tools such as Cortex Code, Claude Code, or similar.
- Experience working in SAFe Agile or another Agile delivery framework.
- Preferred certifications include CDMP, DGSP, DCAM, DAMA-related training, Snowflake certification, Microsoft Power BI certification, or relevant Agile/SAFe certifications.
Competencies
- Knowledge Management Mindset: Helps organize business meaning, definitions, relationships, ownership, and metadata so that enterprise data is easier to find, understand, govern, and reuse.
- Business Partnership: Builds trusted relationships with business and technical stakeholders and translates governance, data quality, and AI-readiness practices into business value.
- Analytical Thinking: Uses structured analysis to evaluate data issues, identify root causes, assess business impact, and improve trust in data used for analytics and AI-enabled capabilities.
- Governance Discipline: Applies consistent standards for definitions, metadata, quality rules, stewardship, lineage, and documentation.
- Communication: Explains complex data concepts clearly to both technical and non-technical audiences.
- Continuous Improvement: Identifies opportunities to improve governance workflows, data usability, automation, AI-assisted documentation and scalable self-service analytics.
Skills & Abilities
- Ability to support semantic layer and metrics governance, including standardized definitions, dimensional concepts, hierarchies, measure consistency, and policy adherence.
- Familiarity with knowledge management concepts such as ontologies, knowledge graphs, taxonomies, and domain models.
- Ability to translate technical data structures into clear, business-aligned definitions and documentation, especially via data dictionaries, catalog entries, report inventories, data quality findings, and usage context.
- Strong SQL skills for data profiling, validation, reconciliation, and issue investigation.
- Familiarity with Snowflake, SQL Server, Power BI, Tableau, SSRS, data catalogs, modern analytics platforms, and open lakehouse concepts such as cloud object storage, open table formats, metadata catalogs, and governed data access.
- Ability to work effectively across business, analytics, data engineering, platform, stewardship, and leadership teams.
- Practical understanding of healthcare data domains such as claims, membership, providers, clinical operations, pharmacy, quality, utilization management, or finance preferred.
- Ability to manage multiple priorities in an Agile environment while maintaining attention to detail.
- Awareness of emerging automation, AI-assisted documentation, data quality monitoring, semantic search, and governed by self-service analytics capabilities.
What's in it for you?
Base Salary Range: $80,300 to $138,330 annually
An annual employee bonus program
Robust Wellness Program
Generous paid-time-off (PTO)
11 paid holidays per year, 1 floating holiday, birthday off, and 2 volunteer days
Excellent 401(k) Retirement Saving Plan with employer match
Robust employee recognition program
Tuition reimbursement
An opportunity to become part of a team that makes a difference to our members and our community every day!
We're always looking for talented people to join our team! Qualified applicants are encouraged to apply now!
At SCAN we believe that it is our business to improve the state of our world. Each of us has a responsibility to drive Equality in our communities and workplaces. We are committed to creating a workforce that reflects our community through inclusive programs and initiatives such as equal pay, employee resource groups, inclusive benefits, and more.
SCAN is proud to be an Equal Employment Opportunity and Affirmative Action workplace. Individuals seeking employment will receive consideration for employment without regard to race, color, national origin, religion, age, sex (including pregnancy, childbirth or related medical conditions), sexual orientation, gender perception or identity, age, marital status, disability, protected veteran status or any other status protected by law. A background check is required.
#LI-JB1 #LI-Hybrid
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information. 41 CFR 60-1.35(c)
See All 595+ AI Analyst Jobs
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Find AI Analyst JobsAI Analyst Job Market
Who's Hiring
- Booz Allen Hamilton21
- JPMorganChase14
- Google9
- Johns Hopkins University Applied Physics Laboratory9
- Amazon8
Top Industries Hiring
- Technology & Software13
- Education10
- Banking & Financial Services8
- Healthcare & Medical Services6
- Investment & Asset Management5
What Employers Look For
The qualifications that appear most often in AI analyst jobs.
- Proficiency in Python or R for data manipulation, modeling, and analysis
- Experience with machine learning frameworks such as scikit-learn, PyTorch, or TensorFlow
- Ability to write and optimize SQL queries against large relational databases
- Familiarity with cloud data platforms such as AWS, Azure, or Google Cloud
- Strong skills in data visualization tools such as Tableau, Power BI, or similar
- Bachelor's degree in data science, computer science, statistics, or a related quantitative field
Tips for Your AI Analyst Job Search
Quantify model impact on your resume
AI Analyst resumes that name the business outcome of a model outperform generic ones. Instead of listing tools, write what your work improved: accuracy rate, processing time, or revenue lift. Hiring managers scan for measurable results, not just Python and TensorFlow.
Apply early to roles that fit
Migrate Mate lists ai analyst openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Tailor applications to the data stack
Job postings for ai analyst roles often signal the team's stack in the requirements section. If you see Databricks, Snowflake, or BigQuery called out, mirror that language in your application materials so your resume clears automated screening before a human reads it.
Build a public project portfolio
Many ai analyst candidates lose out to peers who show work, not just claim it. A public repository with two or three end-to-end projects, documented with business context and methodology, gives hiring managers something concrete to evaluate before the first call.
Prepare for a technical take-home case
AI Analyst interviews frequently include a take-home assignment where you clean a messy dataset, build a model, and present findings to a non-technical audience. Practice narrating your analytical choices out loud, not just producing accurate outputs.
Negotiate scope, not just compensation
When you receive an offer, ask which data systems you'll own, how decisions get made about model deployment, and what the roadmap looks like. These answers reveal whether the role is analytical or mostly reporting, which affects your growth and your leverage in future negotiations.
AI Analyst Jobs: Frequently Asked Questions
Which companies are hiring the most ai analysts?
Booz Allen Hamilton, JPMorganChase, and Google are hiring the most ai analysts right now, with openings concentrated in Texas, California, and Virginia, based on current listings on Migrate Mate as of November 2026. Demand is especially strong at technology companies, financial services firms, and large healthcare systems integrating AI into their operations.
How many ai analyst jobs are remote?
About 69% of ai analyst openings are fully remote or hybrid as of November 2026, reflecting strong demand for distributed analytical talent. Roles focused on natural language processing, model monitoring, and business intelligence reporting tend to be the most remote-friendly, while positions requiring hands-on collaboration with engineering or product teams more often require some in-office presence.
How do you become an ai analyst?
Start by building a foundation in statistics, programming, and machine learning through a degree in a quantitative field or rigorous self-study. Develop hands-on experience with real datasets through personal projects, open-source contributions, or internships. Then target entry-level roles with titles like junior data analyst or machine learning analyst to build applied experience before moving into dedicated ai analyst positions.
How do you get hired as an ai analyst with little experience?
Focus on demonstrating applied skills rather than credentials alone. Build two or three portfolio projects that solve a recognizable business problem using publicly available data, document your methodology clearly, and publish the work. Roles at smaller companies, startups, or in industries early in their AI adoption, such as local government, education, or regional healthcare, often have less competition and more willingness to develop junior candidates.
What does the ai analyst interview process look like?
Most ai analyst interview processes include an initial recruiter screening, a technical phone or video interview covering statistics and machine learning concepts, a take-home case study or coding challenge, and a final panel interview with data science leads and business stakeholders. Some companies add a presentation round where you walk through your case study findings and defend your analytical choices to a mixed technical and non-technical audience.
Where can I find and apply to ai analyst jobs?
You can find and apply to ai analyst jobs on Migrate Mate, which lists current openings from companies across the United States. Search the listings to find roles that match your skills, seniority level, and location preferences, then apply directly to each listing that fits.
See All 595+ AI Analyst Jobs
Find roles that match your experience and apply in just a few clicks.
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